Outsmarting HIV With Vaccine Antigens Made to Order

AIDS vaccine researchers may be one step closer to outwitting HIV, thanks to designer antibodies and antigens made to order at Duke.

HIV was identified as the cause of AIDS in 1983. Despite decades of progress in understanding the virus, an effective vaccine remains elusive.

The lack of success is partly due to HIV’s uncanny ability to evade the immune system.


Duke graduate student Mark Hallen and his advisor, Duke computer science and chemistry professor Bruce Donald. Hallen was awarded a 2015 Liebmann Fellowship for graduate studies.

Now, a team of researchers including Duke computer scientist Bruce Donald and graduate student Mark Hallen have published a 3-D close-up of a designer protein that, if injected into patients, could help the immune system make better antibodies against the virus — a step forward in the 30-year HIV vaccine race.

Led by structural biologist Peter Kwong at the Vaccine Research Center in Bethesda, Maryland, the team’s findings appeared online June 22 in the journal Nature Structural & Molecular Biology.

More than 35 million people worldwide are living with HIV, and about two million more people are infected each year.

Antiretroviral drugs can prevent the virus from reproducing in the body once someone is infected, but only a vaccine can stop it from spreading from one person to the next.

Vaccines work by triggering the immune system to make specialized proteins called antibodies, which prime the body to fight foreign substances. But in the case of HIV, not all antibodies work equally well.

One reason is that HIV is always mutating in the body.

3D print of HIV. Thousands of times smaller than the width of a human hair, the virus is covered with proteins (purple) that enable it to enter and infect human cells. Photo by Daniel Mietchen via Wikimedia Commons.

3D print of HIV. In real life the virus is thousands of times smaller than the width of a human hair. HIV is covered with proteins (purple) that enable it to enter and infect human cells. Photo by Daniel Mietchen via Wikimedia Commons.

HIV incorporates its genetic material into the DNA of its host, hijacking the cell’s replication machinery and forcing it to make more copies of the virus. Each round of replication generates small genetic “mistakes,” resulting in slightly different copies that the host’s antibodies may no longer recognize.

Even before the body makes an antibody that works against one strain, the virus mutates again and makes a new one.

“It’s a race against a moving target,” said Hallen, who was also an undergraduate at Duke majoring in chemistry and mathematics.

In the early 1990s, researchers discovered that a tiny fraction of people infected with HIV are able to produce antibodies that protect against many different strains at once.

These “broadly neutralizing antibodies” fasten to the virus’s surface like a key in a lock and prevent it from invading other cells.

But HIV can evade detection by these powerful antibodies, as the part of its outer coat that is vulnerable to their attack is constantly changing shape.

To overcome this problem, first the researchers needed a close-up look at the region of interest — a spike-shaped virus protein known as Env — in its most vulnerable state.

A 3-D closeup of a key virus protein frozen in a shape the researchers say could serve as a template for a vaccine. Image courtesy of Bruce Donald.

A 3-D closeup of a key virus protein frozen in a shape the researchers say could serve as a template for a vaccine. Image courtesy of Bruce Donald.

With this 3-D blueprint in hand, Hallen and former Duke PhD Ivelin Georgiev developed a scoring system and rated dozens of antibodies according to how well they bound to it. They confirmed that the specific conformation of the Env protein they identified was visible to effective antibodies but not ineffective ones.

The team then identified amino acid sequence changes that would freeze the protein in the desired shape.

Once locked in place, the researchers say, the protein could be injected into patients and used to coax their immune systems into preferentially churning out only the most effective antibodies.

“The idea is to ‘tie’ the protein so that it can’t transition to some other conformation and elicit ineffective antibodies as soon as the effective antibodies bind,” Donald said.

Support for this research included grants from the US National Institutes of Health, the US National Institutes of General Medical Sciences, the US National Institute of Heart, Lung and Blood, the US National Science Foundation and the Bill and Melinda Gates Foundation.

CITATION: “Crystal Structure, Conformational Fixation and Entry-Related Interactions of Mature Ligand-Free HIV-1 Env’,” Kwon, Y. et al. Nature Structural & Molecular Biology, June 22, 2015. DOI: 10.1038/nsmb.3051.



Robin Smith joined the Office of News and Communications in 2014 after more than ten years as a researcher and writing teacher at Duke. She covers the life and physical sciences across campus.



Summer Data+ Groups Pursue Pigs and Purchases

Many students spend their summer breaks going on vacations and relaxing, but not the 40 students selected to participate in Data+, a summer research program at Duke.

They meet twice a week for lunch to share their work on the third floor of Gross Hall.

A pair of pigs and their piglets. Photo by Alan Fryer via Wikimedia commons

A pair of pigs and their piglets. Photo by Alan Fryer via Wikimedia commons

Mercy Fang and Mike Ma are working on a research project involving prolific pigs, those that make a lot of piglets. They are trying to determine if the pigs are being priced rationally, whether or not the livestock market is efficient and the number of offspring per pig.

Fang said the most challenging part is the research data. “Converting PDF files of data into words has been hard,” said Fang.
The students are using four agricultural databases to determine the information on the pigs, including pedigrees.

Most of the students in Data+ are rising sophomores and juniors majoring in a variety of majors that include math, statistics, sociology and computer science. The program started in mid-May and runs for 10 weeks and allows students to work on projects using different research methods.

Another group of student that presented on June 18 is working on a research project involving data on food choices.

A produce stand in New York City, photo by Anderskev via Wikimedia Commons.

A produce stand in New York City, photo by Anderskev via Wikimedia Commons.

Kang Ni, Kehan Zhang and Alex Hong are using quantitative methods of study using the “clustering process” to determine a recommendation system for consumers to help them choose healthier food choices. The students are working with The Duke-UNC USDA Center for Behavioral Economics and Healthy Food Choice Research (BECR) center.

“Consumers already recognize a system to get a certain snack,” said Zhang. “We want to re-do a system to help consumers make better choices.”

The students are basing their research on nutrition information and food purchases from the BECR Data warehouse, which comes from consumer information from throughout the US. This includes food purchases and nutrition information from 2008-2012.

Zhang added that the hardest part was keeping up with information.
“It’s a lot of data in the future, and it will be challenging putting it into use,” said Zhang.

Students in attendance said the food choices data research group provided good information.

“I liked the quantitative methods they used to categorize food,” said Ashlee Valante.

The Data+ research program is sponsored and hosted by the Information Initiative at Duke (iiD) and the Social Science Research Institute (SSRI).  The funding comes from Bass Connections and from a National Science Foundation grant managed by the Department of Statistical Science.

Guest post by Shakira Warren, NCCU Summer Intern

So You Want to Be a Data Scientist

Ellie Burton’s summer job might be described as “dental detective.”

Using 3-D images of bones, she and teammates Kevin Kuo and GiSeok Choi are teaching a computer to calculate similarities between the fine bumps, grooves and ridges on teeth from dozens of lemurs, chimps and other animals.

They were among more than 50 students — majoring in everything from political science to engineering — who gathered on the third floor of Gross Hall this week for a lunch to share status updates on some unusual summer jobs.

The budding data scientists included 40 students selected for a summer research program at Duke called Data+. For ten weeks from mid-May to late July, students work in small teams on projects using real-world data.

Another group of students is working as high-tech weather forecasters.

Using a method called “topological data analysis,” Joy Patel and Hans Riess are trying to predict the trajectory and intensity of tropical cyclones based on data from Hurricane Isabel, a deadly hurricane that struck the eastern U.S. in 2003.

The student teams are finding that extracting useful information from noisy and complex data is no simple feat.

Some of the datasets are so large and sprawling that just loading them onto their computers is a challenge.

“Each of our hurricane datasets is a whopping five gigabytes,” said Patel, pointing to an ominous cloud of points representing things like wind speed and pressure.

They encounter other challenges along the way, such as how to deal with missing data.

Andy Cooper, Haoyang Gu and Yijun Li are analyzing data from Duke’s massive open online courses (MOOCs), not-for-credit courses available for free on the Internet.

Duke has offered dozens of MOOCs since launching the online education initiative in 2012. But when the students started sifting through the data there was just one problem: “A lot of people drop out,” Li said. “They log on and never do anything again.”

Some of the datasets also contain sensitive information, such as salaries or student grades. These require the students to apply special privacy or security measures to their code, or to use a special data repository called the SSRI Protected Research Data Network (PRDN).

Lucy Lu and Luke Raskopf are working on a project to gauge the success of job development programs in North Carolina.

One of the things they want to know is whether counties that receive financial incentives to help businesses relocate or expand in their area experience bigger wage boosts than those that don’t.

To find out, they’re analyzing data on more than 450 grants awarded between 2002 and 2012 to hundreds of companies, from Time Warner Cable to Ann’s House of Nuts.

Another group of students is analyzing people’s charitable giving behavior.

By looking at past giving history, YunChu Huang, Mike Gao and Army Tunjaicon are developing algorithms similar to those used by Netflix to help donors identify other nonprofits that might interest them (i.e., “If you care about Habitat for Humanity, you might also be interested in supporting Heifer International.”)

One of the cool things about the experience is if the students get stuck, they already know other students using the same programming language who they can turn to for help, said Duke mathematician Paul Bendich, who coordinates the program.

The other students in the 2015 Data+ program are Sachet Bangia, Nicholas Branson, David Clancy, Arjun Devarajan, Christine Delp, Bridget Dou, Spenser Easterbrook, Manchen (Mercy) Fang, Sophie Guo, Tess Harper, Brandon Ho, Alex Hong, Christopher Hong, Ethan Levine, Yanmin (Mike) Ma, Sharrin Manor, Hannah McCracken, Tianyi Mu , Kang Ni, Jeffrey Perkins, Molly Rosenstein, Raghav Saboo, Kelsey Sumner, Annie Tang, Aharon Walker, Kehan Zhang and Wuming Zhang.

Data+ is sponsored by the Information Initiative at Duke, the Social Sciences Research Institute and Bass Connections. Additional funding was provided by the National Science Foundation via a grant to the departments of mathematics and statistical science.

Writing by Robin Smith; video by Christine Delp and Hannah McCracken


Bird Consortium Wants to Run the Table

Just a few months after rolling out a huge package of studies on the genomics of 48 members of the bird family tree, an international consortium of scientists is announcing their new goal: sequencing all 10,000 species of birds in the next five years.

Erich Jarvis

Erich Jarvis is an associate professor of neurobiology in the medical school and a Howard Hughes Medical Institute investigator.

Called B10K for short, this effort should be the first attempt to sequence the genomes of all living species in a single class of vertebrates – and the most species-rich one at that.

The consortium announced their intentions in a letter appearing June 4 in Nature.

A genomic-level tree of life of the entire class should reveal links between genetic and phenotypic variation, perhaps reveal the evolution of biogeographical and biodiversity patterns across a wide-range of species, and maybe show the influences of ecology and human activity on species evolution.

But consortium co-leader, Erich Jarvis of Duke neurobiology, just loves birds for their minds. He is involved with the project to enhance his use of songbird brains as models of human speech.

Having proven the technical feasibility of the project and redrawn the bird phylogeny already, the consortium is now expanding to include experts in museum science, biogeography and ecology from the Kunming Institute of Zoology and Institute of Zoology of Chinese Academy of Science in Beijing; the Smithsonian Institution in the USA; and the Center of Macroecology, Evolution and Climate in Denmark. The complete list of contributing institutions and collaborators is listed on the B10K site.

B10K bird phylogeny

The new bird family tree drawn on complete genome sequencing of 48 species representing each major order. Painting by Jon Fjeldså.

“Given the small size and less complex features of bird genomes relative to other vertebrates, the ongoing advances in sequencing technologies, and the extensive availability of high quality tissue samples from birds deposited in museums around the world, reaching this ambitious goal is not only possible but also practical,” the consortium said in a prepared statement.

We look forward to many more exciting findings from B10K, but hopefully not all at once like last time.

-By Karl Leif Bates

Two Duke Teams Attempting to Map LinkedIn Universe

LinkedIn, the social media platform for career-related connections, has a huge problem.  The company has a grand vision of making the world economy more efficient at matching workers and jobs by completely mapping the data its 364 million users have posted about their skills, work history, education and professional networks.


The LinkedIn network of blogger Dr. Stephen Chan, circa 2013. (click to view larger)

But that turns out to be a much more gnarly problem than anyone expected. So, the company has done the Internet-age thing and crowd-sourced it.

Two Duke teams are among 11 selected last month from hundreds of proposals to participate in the company’s economic graph challenge. Selection means each team gets $25,000 (not quite enough for one grad student), a special secure LinkedIn laptop granting access to “a monitored sandbox environment,” and a mentor within the company who will stay in regular contact.

They’re supposed to deliver results in a year.

David Dunson of Duke

David Dunson, professor of statistical science

A Duke team lead by statistics professor David Dunson seeks to draw a richly detailed 3-D map of the network, making connections by education, skill set, employers and so on. “That’s incredibly difficult,” Dunson said. “With hundreds of millions of users, even a simple network would have 100 million-squared nodes, which is absurd.” His team hopes to develop algorithms to break the computation problems into manageable chunks.

This project, called “Find and change your position in a virtual professional world,” also includes statistics PhD student Joseph Futoma and Yan Shang, a PhD student in operations management at the Fuqua School of Business.

Katherine Heller, assistant professor of statistical and computer science

Katherine Heller, assistant professor of statistical and computer science

The other team is trying to pair whole-language analysis of user profiles with a three-dimensional map of a user’s network to speed job connections.

“We could have an awesome algorithm, but if it takes the age of the universe to run: ‘Hey, we’ve got a job for you — if you’re still alive!’” said Katherine Heller, an assistant professor of statistics and computer science. Her team, “Text Mining on Dynamic Graphs” also includes David Banks, professor of the practice in statistical science, and statistics PhD student Sayan Patra.

What the Duke teams are most excited about is the chance to tackle real-world data on a scale that few academics ever get a chance to work with. “These data are super-more interesting,” Dunson said. “It’s amazing to think of all the different things you could do with it.” If the academic teams come up with good solutions, they might be tools that could be used on other big-data problems, he added.

Even if the problems aren’t solved, LinkedIn’s contest has also built a good connection to the Duke campus, Heller notes. “It gives them access to seeing what’s going on in the department and possibly meeting some of the students,” she said.

And that’s the sort of thing that might lead to some new career connections.


LinkedIn logo in their offices. (photo by Search Engine Journal)

-By Karl Leif Bates

What Affordable Art Can Tell Us About Taste

Art historians look beyond the big buyers of 18th century paintings

By Robin A. Smith

Coverage of the art market tends to focus on the highest-priced works, like this painting by Paul Gauguin, which fetched a record-breaking $300 million in 2015. A new Duke study goes beyond the biggest bidders and the most prominent artists to better understand the factors that drive the price of art.

Coverage of the art market tends to focus on the highest-priced works, like this painting by Paul Gauguin, which fetched a record-breaking $300 million in 2015. Duke researchers are delving beyond the biggest bidders and the most prominent artists to better understand what factors drive the price of art.

Of the billions of dollars of art bought and sold at auctions in New York, London, Paris and Hong Kong this spring, most of the buzz has centered on the highest-priced works. But these are a tiny fraction of what’s up for sale.

An analysis of thousands of painting sales in 18th century Paris looks beyond the top sellers to find out why people were willing to pay more for some works of art than others.

It turns out that then, as now, marketing meant a lot.

“Previous research has tended to focus on the tastes of the most prominent collectors as if they applied to all buyers,” said Duke University art historian Sandra van Ginhoven. “But looking only at the highest-priced paintings does not reveal the full scope of the market. We wanted to go beyond the big names.”

Van Ginhoven and doctoral student Hilary Cronheim of the Duke Art, Law and Markets Initiative analyzed auction catalogs and sales records from art auctions held in Paris over 16 years from 1764 to 1780, compiling a dataset of nearly 3400 paintings.

Unlike the glossy sales catalogs produced by auction houses today, the auction catalogs of the 1700s included text descriptions but no images of the art for sale. Potential buyers had to rely on the descriptions alone, sight unseen, much like a restaurant menu.

By scouring the descriptions of each painting in the sales catalogs that dealers distributed to potential buyers in the months before the auctions, the researchers were able to characterize each painting along 30 traits, including school, dealer and subject matter.

The most expensive painting in the data set was "The Prodigal Son," by David Teniers, which sold for 29,000 French livres.

The most expensive painting in the data set was “The Prodigal Son,” by David Teniers, which sold for 29,000 French livres.

Analyzing the data with Duke statistician Mine Çetinkaya-Rundel and the 16 students in her course, “Sta 112: Better Living with Data Science,” turned up some surprising results.

Dutch and Flemish paintings commanded some of the steepest prices, bringing in 50 percent more on average than other paintings.

Among the most coveted works was a 1776 painting by top-selling Flemish artist David Teniers, whose “Prodigal Son” fetched a whopping 29,000 French livres.

At the other end of the spectrum were works like a 1768 painting of three rabbits on canvas by an unknown French artist, which was a bargain at one livre, or roughly the price of a gallon of wine.

“The prices varied a lot,” van Ginhoven said.

While the average sale price was 891 livres, half of the paintings auctioned in Paris in the late 1700s sold for 150 livres or less.

While a fraction of the paintings fetched 10,000 livres or more, the vast majority of the paintings sold for less than 200 livres, like this flower still life by Jean-Baptiste Monnoyer.

While a fraction of the paintings fetched 10,000 livres or more, the vast majority of the paintings sold for less than 200 livres. Flower still life by Jean-Baptiste Monnoyer.

By including these less expensive works by little-known or underappreciated artists and the people who bought them, the researchers were able to get a more complete picture of what drove sales.

Font size mattered, for one.

Using a supersized font in the catalog descriptions to draw attention to certain aspects of a painting, such as its polished finish, boosted sales. Buyers were willing to pay almost six times more for a painting described in big, bold lettering than one described in a normal font.

“It was a very conscious decision on the part of the dealers,” van Ginhoven said. “One dealer started doing it and then it spread to other dealers because it was such a successful marketing strategy.”

Including information about the chain of ownership brought higher bids, too. The tactic was new at the time. Dealers soon discovered that buyers were willing to pay twice as much for a painting when they knew who the previous owner was.

“It meant the painting had already been vetted,” van Ginhoven said.

The researchers shared their findings at the 2015 College Art Association conference in New York in a session titled, “The Meaning of Prices in the History of Art.”


What Happens When a Language Goes Silent?

Writing by Alison Jones; Art by Jonathan Lee

Over the millennia, some 7,000 human languages evolved around the world. Now that number is shrinking. with another language going extinct about every two weeks. By century’s end, the number of human languages could be cut in half, says linguist Julie Tetel Andresen.

When a language dies, we lose practical information about flora and fauna – and  something more intangible, says Andresen, professor of English and chair of linguistics at Duke. She is donating profits from her forthcoming book to help preserve threatened languages around the globe.

Check out five hotspots where languages are disappearing at the fastest pace, and learn about revival efforts that could keep some languages alive:

Read the full story on Duke Today.


Brain Institute Goes Underground

By Karl Leif Bates

From the top side, it looks like a miniature of the landmark Apple store on Fifth Ave. in Manhattan — a simple glass cube.


The entrance to the new DIBS space is just a glass box on the plaza next to LSRC.

But descending the stairs or the glass elevator brings one into the newest, hippest space on campus, the new headquarters of the Duke Institute for Brain Sciences (DIBS). DIBS opened the new underground space at the Levine Science Research Center (LSRC) this week with a reception and lecture.

(The inaugural lecture by Sarah-Jayne Blakemore of University College London, was about her work on the adolescent brain. The peak volume of gray matter in the human brain comes around age 14 and then declines, Blakemore says, but that’s not all a bad thing. It’s the pruning and streamlining of connections that turns a socially obsessed, impulsive teenager into a confident, somewhat-rational adult.)

DIBS atrium

The atrium of the new center feels spacious, despite being underground.

The 11,000-square-foot space stretches south from the cube and  beneath the Blue Front dining hall in a big bay that used to house utilities equipment for LSRC. The ceilings still boast giant pipes marked CHILLED WATER and such, but the rest of it is comfortable, ultra-modern space for brain scientists to communicate, collaborate and learn, with space-saving sliding doors on the offices, and glass garage doors to section off or open up the meeting rooms.

There are actually two levels in the new lair. The mezzanine, ringed by a groovy steel-cable balustrade, provides offices,  a conference room, and even a sort of balcony overlooking the main events space where Blakemore spoke.

DIBS lecture hall

The lecture hall is a flexible space with a ‘balcony’ of sorts.

The main level below is larger and has more staff offices, two teaching labs, and an airy atrium topped with big ring-shaped light fixtures. A divisible “team room” can be used for Bass Connections meetings or other gatherings, and an even larger multi-function space is set up for lectures, but has a flat floor and stackable chairs, so it could do lots of other things too.

There’s even a little room between the teaching labs that might come in handy for storing brains, DIBS Director Michael Platt points out on an introductory tour.

“We haven’t come up with a name yet,” Platt says. “It’s been called the DIBS underground, the Cube…” Standing nearby, psych and neuroscience professor Scott Huettel offers, “We could call it the voxel,” a cubic measure often used in MRI studies.

Michael and Zab

DIBS Director Michael Platt and Associate Director Zab Johnson designed the new space.

The orange walls on the lower level offices don’t go all the way to the ceiling, which helps it feel less underground but may require some new telephone and meeting etiquette, says communication director Julie Rhodes.

“We’re thrilled with it,” said DIBS Associate Director Elizabeth “Zab” Johnson, who co-designed the space with Platt and has already relocated her office from LSRC to the still-unnamed new space.

A Gutsy Approach to Lemur Science

By Sheena Faherty, biology Ph.D. candidate

Can the microorganisms living in a baby lemur’s gut help it grow up to be a vegetarian or an omnivore?

A new study appearing May 13 in Plos One shows that baby lemurs’ gut bacteria have different, diet-dependent strategies for reaching adult mixtures of microbes.  This, in turn, might contribute to why some lemurs are strictly leaf-eaters, while some nosh on just about everything.

lemur eating flowers

A black and white ruffed lemur (Varecia variegata) finds North Carolina’s vegetation as delicious as it is beautiful. (Duke Lemur Center, David Haring)

Erin McKenney, lead author on the study and a Ph.D. candidate in the Biology department, is looking at the patterns of how the bacteria colonize the gut of their lemur host and why this is essential for helping the adult lemurs navigate their environment — and their diets.

“This study is important because all mammals are born with basically sterile guts,” McKenney said. “But by the time we’re adult mammals, there are 20 trillion bacteria living in the gut. (The bugs are an) adaptive super organ that has co-evolved with the host and dictated the host’s evolution. We want to know more about how that happens.”

This “microbiome” of the gut is a jack-of-all-trades, performing jobs like protecting the host’s body from pathogens and helping it digest food. When the gut’s microbes digest foods that are high in fiber — like plant matter — some of the digestion by-products are absorbed by the intestine, which provides nutrition for the body. Humans get up to 10 percent of our daily nutritional requirements from fiber breakdown by bacteria.

Erin McKenney

Erin McKenney scooping lemur poop for SCIENCE!

“Mammals don’t secrete the enzymes that are necessary, so no mammal can digest fiber on its own,” McKenney said. “These microbes are performing an incredibly important life process for us.”

At the Duke Lemur Center, McKenney collected fecal samples from three different species of lemur that evolved to eat different foods—a strict leaf-eater, and two omnivores. Using DNA sequencing, she determined the communities of bacteria that are living in their guts at different life stages from birth to adulthood.

Watching microbiomes through time may enable her to answer the question of how the microbiome of each species becomes teeming with 20 trillion bacteria, and if the patterns differ based on diet.

lemur eating pokeweed

Vegetarian lemurs can eat a surprising variety of stuff we’d find nasty, like pokeweed and even poison ivy. (Duke Lemur Center, David Haring)

The results suggest that all species of baby lemurs, when they are born and nursing from their mothers have similar microbiome profiles that are much less complex than adult profiles. But leaf-eaters that eat the most fiber show adult microbiome profiles as soon as solid foods are introduced, which is in contrast to the other two species that take longer to reach adult microbiome profiles. Additionally, leaf-eaters have more complex microbial communities, which allows them to digest fiber-rich foods.

“So when you start to think about the really big picture, beyond everything the gut microbes do for the hosts they live inside of, we find the microbes have done an incredible service to mammalian speciation. The only way that we have leaf-eaters is because of these gut microbes,” McKenney said.